Question 2Consider the scatterplot:unit pressure diff5 10 15 200901-unit pressure diff vs effectiveness-1000O-0.9803100.41428O-0.6995400.98048O-0,41483O-0.01014100200effectivenessThe correlation coefficient between effectiveness and unit pressure diff is closest to:The regression line slope between effectiveness and unit pressure diff is closest to:O-0.04202O-1.956770168226O-5.5391The regression line y-intercept is closest to:0601.23937O-99.7372504.99370799.49646

Given the scatterplot between effectiveness and unit pressure difference as

Answered: Consider the scatterplot: unit pressure…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.5: Correlation And Causation

Problem 2AGP

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Noise and Intelligibility Audiologists study the intelligibility of spoken sentences under different noise levels. Intelligibility, the MRT score, is measured as the percent of a spoken sentence that the listener can decipher at a cesl4ain noise level in decibels (dB). The table shows the results of one such test. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Find the correlation coefficient. Is a linear model appropriate? (d) Use the linear model in put (b) to estimate the intelligibility of a sentence at a 94-dB noise level.
XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict the stock price to be in January 2012? January 2013?
For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
We wish to determine if there is a correlation between the birth weight (in grams) of nine newborn infants and the length of their mothers’ stay (in days) in the hospital. The results of a correlation and regression analysis are indicated in the Excel output below. The mean birth weight of the newborn infants (the independent variable) was 3162.5 grams, and the mean length of their mothers’ stay in the hospital (the dependent variable) was 7 days. SUMMARY OUTPUT Regression Statistics Multiple R 0.862675 R Square 0.744208 Adjusted R Square 0.707666 Standard Error 6.02142 Observations 9 ANOVA df SS MS F Significance F Regression 1 738.4198 738.4198 20.36599 0.002756 Residual 7 253.8025 36.25749 Total 8 992.2222…
A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: ??=?+????+????+???I Where FR = yearly foreign reserves ($000’s), OIL = annual oil prices, EXP = yearly total exports ($000’s) and FDI = annual foreign direct investment ($000’s). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 Oil 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 * 0.0057 FDI -396.99 160.66 -2.471 ** S = 2.45 R – sq = 96.3% R – sq (adj) = 95.3% Analysis of Variance Source DF SS MS F P Regression 3 1991.31 663.77 ? ?? Error 12 77.4 6.45 Total 15 e) Perform the F Test making sure to state…
Please help me with question d, e, f, g, h, and I. Thank you.

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